code: def _export_and_load_model(
      experiment_id: int, master_url: str
  ) -> None:
      # Normally verifying that we can load a model would be a good unit test, but making this an e2e
      # test ensures that our model saving and loading works with all the versions of tf that we test.
      ckpt = (
          client.Determined(master_url)
          .get_experiment(experiment_id)
          .top_checkpoint()
      )
      _ = keras.load_model_from_checkpoint_path(ckpt.download())
  
file_path: determined/e2e_tests/tests/experiment/test_tf_keras.py
imports: import multiprocessing
  from typing import Callable
  import pytest
  from determined import keras
  from determined.experimental import client
  from tests import config
  from tests import experiment
label_desc: Use image node_id 1 for calling a global function with example usage: _export_and_load_model(experiment_id, master_url) without return types